慢性肾脏病患者心率变异性相关影响因素及预防对策 |
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引用本文: | 余福海,沈才杰,陆曹杰,赵馥,王健,张丹. 慢性肾脏病患者心率变异性相关影响因素及预防对策[J]. 中华全科医学, 2021, 19(5): 798-800,855. DOI: 10.16766/j.cnki.issn.1674-4152.001920 |
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作者姓名: | 余福海 沈才杰 陆曹杰 赵馥 王健 张丹 |
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作者单位: | 1.宁波市奉化区人民医院肾内科,浙江 宁波 315500 |
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基金项目: | 浙江省医药卫生科研项目2019KY642 |
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摘 要: | 目的 分析慢性肾脏病(chronic kidney disease,CKD)患者心率变异性(heart rate variability,HRV)的变化情况及影响因素,以期进行针对性干预.方法 选取2017年3月-2019年3月期间收治宁波市第一医院及奉化区人民医院的CKD患者138例作为研究对象,采用MARS动态心电...
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关 键 词: | 慢性肾脏病 心率变异性 影响因素 |
收稿时间: | 2020-06-02 |
Related influencing factors and preventive measures of heart rate variability in patients uffer from chronic kidney disease |
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Affiliation: | Department of Nephrology, People's Hospital of Fenghua District, Ningbo, Zhejiang 315500, China |
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Abstract: | Objective To analyse changes and influencing factors of heart rate variability (HRV) in patients with chronic kidney disease (CKD) for conducting targeted intervention. Methods A total of 138 CKD patients who were admitted to the First Hospital of Ningbo from March 2017 and March 2019 were enrolled as study objects. MARS Holter analysis software and Seer Light ECG box were used to monitor patient' HRV time-domain analysis parameters for 24 h [standard deviation of 5-minute average NN intervals (SDANN), standard deviation of NN intervals (SDNN), the percentage of NN50 in the total number of normal-to-normal intervals (pNN50), square root of the mean of the squared differences between adjacent normal RR (rMSSD)] were detected. The multivariate linear stepwise regression analysis was applied to analyse their influencing factors. Results The results of multiple linear stepwise regression showed that interleukin 6 (IL-6) was an influencing factor of SDANN (t=2.243, P=0.029). Haemoglobin (Hb), C-reactive protein (CRP), IL-6, brachial and ankle pulse wave velocity (baPWV) were influencing factors of SDNN (t=2.084, 3.515, 4.594, 5.523, all P < 0.05). Blood phosphorus and baPWV were the influencing factors of pNN50 (t=2.021, 2.536, all P < 0.05). Hb, IL-6 and serum potassium were the influencing factors of Root Mean Square of the Successive Differences (rMSSD, t=2.156, 4.417, 2.642, all P < 0.05). Conclusion CKD patients are accompanied with decrease of HRV time-domain analysis parameters, which is related to anaemia, micro-inflammation status, electrolyte imbalance and arteriosclerosis. Clinically, intervention can be conducted aiming at the above risk factors. |
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